Context for Reproducibility and Replicability in Geospatial Unmanned Aircraft Systems

Abstract

Multiple scientific disciplines face a so-called crisis of reproducibility and replicability (R&R) in which the validity of methodologies is questioned due to an inability to confirm experimental results. Trust in information technology (IT)-intensive workflows within geographic information science (GIScience), remote sensing, and photogrammetry depends on solutions to R&R challenges affecting multiple computationally driven disciplines. To date, there have only been very limited efforts to overcome R&R-related issues in remote sensing workflows in general, let alone those tied to unmanned aircraft systems (UAS) as a disruptive technology. This review identifies key barriers to, and suggests best practices for, R&R in geospatial UAS workflows as well as broader remote sensing applications. We examine both the relevance of R&R as well as existing support for R&R in remote sensing and photogrammetry assisted UAS workflows. Key barriers include: (1) awareness of time and resource requirements, (2) accessibility of provenance, metadata, and version control, (3) conceptualization of geographic problems, and (4) geographic variability between study areas. R&R in geospatial UAS applications can be facilitated through augmented access to provenance information for authorized stakeholders, and the establishment of R&R as an important aspect of UAS and related research design. Where ethically possible, future work should exemplify best practices for R&R research by publishing access to open data sets and workflows. Future work should also explore new avenues for access to source data, metadata, provenance, and methods to adapt principles of R&R according to geographic variability and stakeholder requirements.

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